Counting bacteria and determining their susceptibility to antibiotics

ABSTRACT

A method for detecting and counting particles suspended in fluids, such as bacteria suspended in urine, utilizing dynamic features of the suspended particles and employing light scattering measurements. The disclosed method is suitable for determining the susceptibility of bacteria to antibiotics. A cuvette for detecting bacteria in fluids, which is especially suited for the light scattering measurements, is provided.

FIELD OF THE INVENTION

The present invention relates in general to assaying biological fluids.In particular the present invention relates to optically testing urinefor detecting, counting bacteria and determining their susceptibility toantibiotics.

BACKGROUND OF THE INVENTION

Biological fluids such as urine, amniotic, pleural, peritoneal andspinal fluids are sometimes subjected to testing for the presence ofbacteria. As a complementary step, it may be required to determine thesusceptibility of such infecting bacteria to antibiotics in order todevise a treatment schedule if an infection is detected. Commonanalytical methods involve culturing and or microscopy, require skilledoperators and are time and resource consuming. Normally, physicians andveterinarians are to wait for days in order to receive laboratoryresults that determine whether a human or animal subject is infectedwith bacteria and recommend the antibiotic most appropriate for therequired treatment.

A method for determining bacterial susceptibility to antibiotic agentswhich is less time demanding is discussed in “Light scattering methodsfor antibiotic sensitivity tests”, by J. Murray, P. Evans and D. W. L.Hukins, in J. Clin Pathol, (1980) 33, 995-1001. This method is based onthe observation that the angle of light scattered from a sample of fluidcontaining bacteria changes after an adequate antibiotic agent is addedto the examined fluid. Two samples of the same fluid, one of which anantibiotic agent, are simultaneously cultured. The culturing time asdisclosed is significantly longer than the half-life time of thebacterial proliferation and is preferably about 90 minutes. Lightscattering measurements across a wide angular range (including backscattering) are carried out for both samples by means of a differentiallight scattering photometer. Representative parameters, such as adisplacement parameter that is proportional to the area separatingbetween the plots of angular scattering profiles of the two samplesdivided by the angular range, are calculated. The values of suchparameters are matched with a calibration scale for determining thesusceptibility of bacteria to a specific antibiotic agent. However theresults of implementing this method are not satisfactory as at least 20%of disagreement between tests attained using the disclosed methodcompared to a common method of incubation and microscopy are reported.

Besides the common culture methods, a number of additional techniqueshave been developed for the determination of the presence of bacteria influids, including, for example, test strips for screening for urinarytract infection (UTI), based on the testing for the presence of productswithin the sample created by infecting bacteria such as nitrite. Howeverthe above-mentioned method fails to detect bacteria that do not generatespecific products. The method requires high bacterial concentration inthe examined sample and therefore such screening process is prone toinsufficient sensitivity and relatively low specificity.

International patent application WO 06018839 A2 discloses a system and amethod for detecting and counting bacteria in such biological fluids.The disclosed method includes the steps of: (1) removing particleslarger in size than the bacteria by filtering a sample of the fluid; (2)measuring the intensity of light scattered from the filtered fluid atone or more points displaced from the axis of the illuminating lightbeam; (3) associating a scattering profile with the scatteringmeasurements; (4) comparing the associated scattering profile withstored reference scattering profiles; (5) bacterial concentration isdetermined by the respective count related to the reference scatteringprofile that fits best the associated scattering profile. The storedbasic profiles according to the disclosed method consists ofstatistically averaged measured and or calculated scattering profilesrelating to calibrated samples of filtered fluids and or linearcombinations of such profiles. A cuvette especially suited for suchlight scattering measurement is also disclosed. Obviously such method iscapable for significantly reducing the time and labor associated withdetecting bacterial infection however the susceptibility of the detectedbacteria to antibiotics remains unsolved.

In U.S. Pat. No. 6,861,230 a method for testing the growthcharacteristics of bacteria including testing bacterial susceptibilityto an antibiotic agent is disclosed. This method combines culturing asample of fluid and luminescence measurements of the cultured sample. Ata preparation stage a sample of the fluid containing the antibioticagent is cultured for a while for generating a base line level of freeadenylate kinase. Bacterial susceptibility is determined by comparinglevels of free adenylate kinase repeatedly measured such that: a firstmeasurement is carried out; then the antibiotic agent is added to theexamined sample, than after a delay of preferably fifteen minutes asecond measurement is made. The level of adenlytate kinase increases incases in which the bacteria are susceptible to the antibiotic agent. Thedisclosed method is reported to be sensitive even in cases in which thebacterial concentration in the examined fluid is considerably low and orthe second measurement of the level of adenylate kinase is delayed by atime interval that is shorter than the preferred time interval. Howeverits implementation requires wet chemistry, culturing and the use ofrelatively sophisticated equipment.

Therefore a rapid and labor saving screening method that can obviate asignificant amount of expensive and time-consuming work in theperformance of the tests is beneficial.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic presentation of a light scattering measurementaccording to the present invention;

FIG. 2 is block diagram describing a system for detecting and countingbacteria according to the method of the present invention;

FIG. 3A is a longitudinal sectional view of a cuvette providing fordetecting bacteria according to a preferred embodiment of the method ofthe present invention;

FIG. 3B is a longitudinal sectional view of a cuvette for detectingbacteria according to another preferred embodiment of the method of thepresent invention;

FIG. 4 is a flowchart describing a process for detecting and countingbacteria and determining their susceptibility to antibiotics;

FIG. 5 is a simulated speckles image of a sample of synthetic urinecontaining bacteria;

FIG. 6 shows exemplary intensity time profiles calculated for bacteriaat a motion;

FIG. 7 is a graph presenting exemplary frequency distributions of thetime dependent intensity of scattered light calculated for one pixel ofa speckles image;

FIGS. 8A and 8B respectively show an intensity—scattering angle—timeprofile of a sample of urine containing E-coli and a sample of urinecontaining PMMA particles;

FIG. 8C shows intensity—time profiles measured at one of the pixelsshown in FIG. 8A;

FIG. 9A respectively shows exemplary graphs of two standard scatteringprofiles, a scattering profile associated to measured intensities oflight scattered by a sample of urine, and a fitted scattering profile,as a function of the scattering angle;

FIGS. 9B and 9C respectively show difference plots computed in twodifferent points in time employing measurements of light scattered froman exemplary sample containing E-coli;

FIG. 9D shows a time profile of an exemplary average derivative of theconcentration of scatterers in time, computed for an exemplary samplecontaining E-coli;

FIGS. 10A and 10B respectively show simulated intensity—scatteringangle—time profiles induced by particles having constant unidirectionalvelocity and by particles having the same unidirectional velocity thatare simultaneously moving in a Brownian motion;

DETAILED DESCRIPTION OF THE PRESENT INVENTION

In accordance with the present invention, a method for counting bacteriasuspended in a fluid is provided. The procedure according to theinvention first employs mechanical filtering of a sample of an examinedfluid followed by measuring intensities of light scattered by thefiltered sample prior to and following an introduction of an antibioticagent. The filtering provides for excluding particles whose sizes exceedthe size of bacteria. The samples of fluid are taken from specimensnormally received in a laboratory for screening bacteria, such asassociated with hospitals and or medical clinics. The examined fluidsaccording to the invention include but are not limited to biologicalfluids, such as urine, amniotic, pleural, peritoneal abdominal andspinal fluids. The received specimen, or the sample of the fluid, neednot be cultured, or chemically treated prior to the test according tothe method of the invention.

Reference is first made to FIG. 1, which schematically shows a setup forlight scattering measurement according to the invention. A coherentlight beam, collimated within a beam volume confined by light rays 10,illuminates particles 12 suspended in a fluid contained in cuvette 14.Point 16 located on a face of light detector 18 is placed aside fromoptical axis 20 by a distance indicated by double arrow 22. Lightscattered by particles within a volume through which the illuminatinglight propagates coherently accumulates to give the intensity of lightmeasured at point 16. Such particles are particles 12, or otherparticles similarly suspended in the fluid. Other possible scatterersare internal discontinuities present within, or particles located on,windows 26 and or the walls of cuvette 14. Light obscuring means 28prevents any direct illuminating light to reach light detector 18. Thescattered light generates a speckles interference pattern on the face oflight detector 18, referred hereinafter by speckles image.

Dynamics of a Speckles Image

Speckles images vary in time due to Brownian motion and or bacterialmotility. The mean value of the magnitude of a velocity of bacteriamoving in a Brownian motion is typically in the range of a few tenths ofmicrometer per second (μm/s) close to 1 μm/s. A typical length of a timeinterval in which such bacteria “forget” their direction is about 10seconds. Motile bacteria can swim substantially linearly at a velocitythat is significantly higher and is far beyond the range of Brownianmotion. The motion of motile bacteria is characteristically interruptedby quiescent periods in which the bacteria tumble and randomly changetheir direction of motion. Furthermore, motile chemotactic bacteria areable to move towards higher concentrations of attractants and avoidhigher concentrations of repellents by sensing temporal changes inchemo-effector concentrations. (An exemplary explanation of bacteriamotility and chemotaxis is given in: “Motile behavior of bacteria”, H.C. Berg, Phys. Today, Volume 53, Issue 1, January 2000, pp. 24-29.)Motile bacteria can also move along a gradient of temperatures in whatis known as thermotaxis. Therefore inducing chemotactic or thermotacticmotion may impact the patterns of the speckle images thereby enhancingthe sensitivity of the detection and measuring a concentration of motilebacteria suspended in fluids, as well as for determining theirsusceptibility to various antibiotic agents, as further described infra.

Features of the System of the Invention

Reference is now made to FIG. 2 schematically showing system 40 that issuitable for counting bacteria according to the present invention. Lightemitted from coherent light source 42, such as a laser source, passesthrough collimator 44 and the collimated beam enters cuvette 46. Lightscattered by particles within cuvette 46 is focused by means ofconverging simple or compound lens 48 to form images across the face oflight detector array 50. Light obscuring means 52 blocks theilluminating beam. Receiver unit 54 controls detector 50, receives,conditions and digitizes signals induced by the scattered light andtemporarily stores them. Processing and control unit 56 provides forcontrolling the test process, receiving data and commands from theoperator, powering light source 42 and receiver unit 54, reading thesignals temporarily stored in receiver unit 54 and for carrying outsignal and data processing. Results of tests and prompts to an operatorare displayed on an operator display, not shown. Dedicated input keyslinked to processing and control unit 56, not shown, provide forentering data and or commands to the system. Optionally processing andcontrol unit 56 transmits data and results of tests to and receives dataand commands from a remote computer. Collimator 44 consists of a simpleor compound lens 58 and one or more diaphragms 60 containing anaperture.

Reference is made to FIGS. 3A and 3B showing longitudinal sectionalviews of a cuvette that is suitable for detecting, counting bacteriaand/or determining their susceptibility to antibiotic agents accordingto two preferred embodiments of the method of the present invention.Light obscuring means 70 is disposed on the inner surface of window 72of cuvette 74. Diaphragm 76 whose aperture is coaxial with obscuringmeans 70 is internally disposed adjacent to window 78. Cuvette 90 isespecially suited for screening tests in which chemotaxis is exhibited.An obscuring means and a diaphragm having an aperture are internallydisposed within cuvette 90 as is described hereinabove. Compartment 92for containing a suitable chemo-effector that is a known attractant or arepellant agent is confined between divider 94 and sidewall 96 ofcuvette 90. Divider 94 has a porous wall facing sidewall 96 and aremovable cover facing lumen 98, both are not shown. The removable coverwhen is placed prevents any transfer of material contained incompartment 92 into lumen 98. Removing the cover off the porous wall,which is firmly attached to cuvette 90, provides for transferring thechemical reagent contained in compartment 92 and dissolving in, ormixing with, the fluid contained in lumen 98. Alternatively, regulatingthe temperature of one or two opposing sidewalls of cuvette 74 effectsinducing a gradient of temperatures across the sample of fluidsproviding for a thermotactic motion.

Cuvettes such as cuvette 74 or 90 are typically mounted in associationwith an external housing including aligning means providing for aligningthe cuvette with the optical axis of the system. Such housing has aninlet for filling compartment 92 with a suitable chemical reagent andanother for filling lumen 96 or the lumen of cuvette 74 with a filteredfluid and or an antibiotic agent. Optionally a cuvette housing isprovided with a filter having pores that are not smaller than the sizesof the bacteria.

The components of a cuvette that are suitable to be employed accordingto the invention are made of materials such as plastic resins typicallyutilized for manufacturing disposable containers for liquids. Suchmaterials that are insoluble in the examined fluids, and are chemicallypassive to the chemical reagents and or the antibiotic agent utilized inthe course of the testing. The windows are transparent in a range ofwavelengths containing the wavelength, or wavelengths, of the source oflight. The windows are made, for example, of plastic typically used formanufacturing optical lenses, glass or quartz. The homogeneity of therefraction index across the window, namely variations in the refractionindex within the window, does not exceed 0.0001. The root mean squarevalue of the surface roughness of the windows does not exceed 1nanometer. Windows having an optical quality of their surfaces definedby a scratch/dig number 40/20 or lower are preferable. According to theinvention, windows made of plastic or glass whose width does not exceed0.5 millimeter is a viable example. The optical homogeneity of the bulkof the window and or its surface roughness impacts the signal to noiseratio of a measured intensity of the scattered light and in turn thesensitivity of the system.

Cuvettes such as cuvette 74 are typically employed for screeningbacteria that are not motile and are referred hereinafter as cuvettes ofthe first type. Cuvettes having a compartment for containing repellantsor attractants such as cuvette 90 are referred to hereinafter ascuvettes of the second type. Further features of the cuvettes that aresuitable for scattering measurements in accordance with the inventionare described in international application WO 06018839 A2 incorporatedherein by reference.

Operating a System of the Invention

Normally a cuvette of the first type is employed for counting bacteriaand determining bacterial susceptibility to antibiotics. Reference isnow made to FIG. 4 showing a flow chart of a process of countingbacteria and determining their susceptibility to antibiotics. Such aprocess includes the following steps: an initialization step 108 inwhich the system and the test program are initialized; a preparationstep 110 in which samples of the fluid are filtered and filled into thetest cuvettes; a test initiation step 112 in which a test cuvette isintroduced into the system and the bacteria are detected and counted; instep 114 an antibiotic agent is manually introduced into the testcuvette; in step 116 light scattering measurements are repeatedlycarried out and processed; in step 118 the system checks whether thetests related to the current specimen of fluids are completed; in step120 the system checks whether the testing of the next antibiotic agentis to be started; in step 121 the system waits for a predefined timebefore carrying out the following session of repeatedly receivingspeckles images; in step 122 the control cuvette related to the currentspecimen of fluids is tested and the system checks in step 124 if thereare more specimens of fluids waiting to be tested; the process iscompleted in step 126.

The process starts in step 108 by manually turning on the processing andcontrol unit by which the system is activated. The operator inputs datarelated to the tests plan and to the specimens, such as the identity ofthe examined fluid, the total number of specimens and the number ofantibiotic agents N_(t) to be examined. The processing and control unitautomatically initiates the test operating program and prompt theoperator to provide relevant data. A queue of the antibiotic agentaccording to a manually updated list of antibiotic agents that aresuitable to the examined fluid is stored in a memory of the processingand control unit. At the end of this program initiation process thesystem stands by and waits for further commands. Meanwhile the operatormanually continues in a preparation (PREP) step 110 in which he performsthe following activities:

(a) mechanically filtering a sample of fluid (b) respectively fillingportions of the filtered fluid into a number of cuvettes. This numberexceeds the number of antibiotic agents to be screened at least by oneserving for control. The remaining cuvettes are the test cuvettes eachof which is dedicated to one of the antibiotic agents. Optionally, suchportions of the raw fluid are pressurized through a filter installed inthe housing of the respective cuvettes to fill them.

In the test initiation (TINIT) step 112 a test cuvette containing afiltered fluid is manually introduced and aligned with the system.Following a manual “start” command the system automatically activatesthe light source (when the first test cuvette of the first specimen offluids is examined) and initiates clocks for measuring time; andrepeatedly receives for a first predefined time interval T₁ a number ofdiscrete speckles images at a predefined exposure time and repetitionrate, which are collectively designated hereinafter by rates CPS₁. Thenthe system prompts the operator to introduce a predefined dose of thefirst agent in the current queue of antibiotic agents into this examinedcuvette. Meanwhile the received speckles images are automaticallyprocessed for “counting bacteria” as further described infra. Theprocessing results are stored in a memory of the processing and controlunit. Then the system automatically pauses and waits for a first“continue” command to switch to step 116. The prompted operatorcontinues in parallel to step 114 in which he manually introduces asuitably calibrated dose of antibiotic agent into the currently examinedcuvette. The operator commands the system to continue to step 116 forperforming repeated scattering measurements (RSM). The system receivesdiscrete speckles images along the same time interval T₁ and at the samerates CPS₁. By the end of this receiving cycle the system initiatesanother clock designated by TT, to measure the time interleaving betweentwo successive receiving cycles. The speckles images just received areprocessed for determining bacterial susceptibility to antibiotics asfurther described infra and the results are stored accordingly. In step118 the system compares the value of T, which is the time elapsed sincethe time a “start” command has been entered to a second time intervalT₂. The time interval T₂ provides for estimating a significant change inthe concentration level of the bacteria due to the antibiotic agent ifany such change occurs. In a case in which the elapsed time T is smallerthan T₂ the system moves to step 120 in which it compares the value ofTT to the third predefined time interval T₃, which is the time intervalseparating between two successive receiving cycles. If TT is smallerthan T₃ the program waits for a while in step 121 and further goes backto check the value of TT compared to T₃ in step 120. Otherwise thesystem goes back to step 116.

In a case that T is not smaller than T₂ the process continues to step122 in which the operator is prompted to replaces the currently screenedcuvette with the control cuvette. The system automatically measures theconcentration of bacteria considering the control cuvette following acontinue command to be entered by the operator. The respective dataconsidering the measurements of the screened and control cuvettes arestored in the memory of the controller and the operator is furtherpresented with the results.

In exceptional cases, such as cases in which discrepancies between theintermediate and or the final results extends beyond a predefinedthreshold, the operator is prompted to partially or entirely repeat thetest process accordingly. At this stage the program automaticallyswitches back to step 110, not shown, where it waits for a “start”command to be manually entered by the operator after completing therespective preparations and modifying the parameters of the systemaccordingly. Normally, the program continues to step 124, as shown, inwhich the system checks if the number N of successfully completed testsis smaller than the total number of samples of fluid N_(T). In a casethat there are more samples waiting to be tested the system prompts theoperator to proceed with preparing a new sample for screening startingat step 110. Meanwhile the system waits for a “start” command, to bemanually entered by the operator when he is ready, to switch to step112. Otherwise the system completes the processing related to the lastsample of fluids and further determines the antibiotic reagent orreagents to which the bacteria detected in the respective cuvette aremostly susceptible as is further described infra. The process iscompleted in step 126 after the data is optionally transmitted to aremote computer.

A process for detecting and optionally counting bacteria according to apreferred embodiment of the present invention is hereby described withreference to the same FIG. 2. However all the steps 114-121 are avoided.By the end of step 112 the program automatically continues to step 122.In step 122 the system computes averaged difference plots which arefurther matched to a stored calibration scale as described infra. Thenin step 124 the system checks whether the number of completed testsexceeds the total number N_(t) of cuvettes to be tested. In a case ofpositive answer the process is completed in step 126 after the operatoris displayed with the results and the data is optionally transmitted toa remote computer. Otherwise the system prompts the operator to replacethe tested cuvette with the following one and switches to wait at thebeginning of step 112 for a new “start” command.

Signal and Data Processing

Background signal originated by particles suspended in the sample offluid that are larger than the bacteria are excluded by mechanicallyfiltering according to the method of the present invention. Howeverthere are sources and light scatterers other than the bacteria that cancontribute a stationary background signal. Such signals are typicallyoriginated by stationary particles present within the illuminated space,impurity of the light source, defects in, and or particlescontaminating, the optical components. Therefore a difference plot iscomputed for excluding stationary background according to a preferredembodiment of the present invention. The intensity measured in everypixel of a speckles image is subtracted from the intensity measured inthe same pixel of a preceding speckles image to form a difference plot.The difference plot is an image having the same number and arrangementof pixels as of a speckles image, whose intensities equal the absolutevalue of the respective differences. Therefore a difference plotdisplays only the time dependent components of the intensity of lightscattered by the examined fluid.

A number of such difference plots are averaged in time and or in one ortwo-dimensional region of scattering angles to form an averagedderivative of the concentration of scatterers in time. Obviouslydifference plots and averaged derivatives are smoother than specklesimages and the rate in which they change in time mainly depends on therate in which the concentration of non-stationary scatterers changes.Typically the dynamic range of difference plots and averaged derivativesis smaller than the dynamic range of the respective speckles images andtheir signal to noise ratio is better.

For counting bacteria first a scattering profile is associated to anaveraged derivative computed for the earlier speckles images receivedwhen examining a test cuvette. Such association is achieved for exampleby a common numerical fitting technique. Alternatively a number of theearliest speckles images received for a test cuvette are similarlyaveraged in time and or in one, or two, dimensional angular region. Ascattering profile is associated to such averaged speckles images byemploying common numerical fitting of curves or three-dimensionalsurfaces. The associated scattering profile is then compared to standardscattering profiles stored in the system. The concentration of bacteriain the examined fluid equals the concentration of the standardscattering profile that best fits the associated scattering profile. Theset of standard scattering profiles constitutes a calibration scale towhich the scattering profiles associated with the measurements arecompared for estimating the bacterial concentration of the examinedfluid.

For determining the susceptibility of bacteria to an antibiotic agent,an average value of at least two averaged derivatives computed first fora test cuvette, immediately following the introduction of an antibioticagent, are compared to an average of the same number of averagedderivatives computed for speckles images received a few minutes later,preferably after more than 5 minutes. The antibiotic agent for which thedifference between these averaged derivatives is the larger isdetermined.

A control count test includes the steps of detection of bacteria anddetermining their concentration. The test is carried out inconsideration with the time elapsed from the examination of the firsttest cuvette, as is described above.

Calibrated scattering profiles are prepared according to a preferredembodiment of the present invention by statistically averagingscattering profiles measured or computed for calibrated specimens offluids containing, and specimens free of, bacteria. Standard scatteringprofiles include calibrated scattering profiles and linear combinationsof calibrated profiles. Calibrated scattering profiles and or standardscattering profiles are pre-stored in the system. Further features ofthe calibrated profiles and standard profiles as well as a more detaileddescription of fitting techniques are described in international patentapplication WO 06018839 A2.

EXAMPLE 1

A simulated analysis of speckles images was conducted. A synthetic modelof urine was prepared in which 2-4 μm diameter spheres having the

same dielectric constant as those of bacteria represent bacteria. Theparticles are randomly distributed in a uniform medium matching anaqueous solution of salt. Randomly distributed spheres whose radius issmaller than one micron and having a matching dielectric constantrepresent salt particles. The synthetic urine is contained within acylinder having a diameter of 0.5 millimetre (mm) and a height of 55 mm.This cylinder conforms a volume separating between the aperture ofdiaphragm 76 and light obscuring means 70 within cuvette 74 shown inFIG. 3A to which reference is again made. The particles are coherently(spatially and temporally) illuminated such as by means of a laserdiode. The intensity of scattered light measured at a point across theface of the light detector is calculated employing coherent ray tracingin which the intensity at the face of the scattering particle conformsthe scattering angular distribution according to the Mie theory. [H. C.van de Hulst. “Light scattering by small particles”, John Wiley & Sonspublishing, NY, 1957].

Reference is now made to FIG. 5 showing a speckles image such calculatedas received across one quadrant of a planar detector array. Theintensity of the scattered light as is shown in FIG. 5 decreases withthe scattering angle conformal with the scattering angular distributionaccording to the Mie theory. The spatial frequency of the specklesincreases with the scattering angle as a larger number of particles,which are randomly distributed, contribute to the speckles interferencepattern.

EXAMPLE 2

An analysis of the dynamics of a simulated speckles image employing thesame physical models and approach as is described in example 1hereinabove was conducted. Reference is now made to FIG. 6 showingexemplary temporal behaviours of the intensity of the scattered lightcalculated at a point on the face of the light detector. The point isspaced 1 mm aside from the optical axis of the system. The particlessuspended in the synthetic urine are moving in uniformly distributeddirections at velocities having normally distributed magnitudes. Plot130 shows a simulated intensity-time profile in which the mean value ofthe magnitude of the velocities is 0.25 μm/sec. Plot 132 shows anothersimulated intensity-time profile in which the mean value of themagnitude of the velocities is 5 μm/sec. The signal intensity receivedby the light detector at this point is measured in arbitrary units(A.U.). The time is given in seconds (SEC). The scale of the signalintensity is linear and Plot 132 is shifted aside from plot 130 (forgraphical purposes). Particles moving in higher speeds cause a segmentof the resulted speckles image to change and flicker at a higher ratethan a similar segment induced by slower particles. Whereas spatiallyfixed particles result a stationary speckles image.

Reference is now made to FIG. 7 showing exemplary frequencydistributions of the time dependent magnitude of a signal received atthe same point as in FIG. 6. The particles move in the fluid atvelocities having uniformly distributed directions and normallydistributed magnitudes. Plots 140-146 show the frequency distributionscorresponding to mean values of 0.25, 0,50, 2.5 and 7.5 μm/secrespectively. Frequencies are measured in Hertz (Hz) and the signalintensities measured in A.U. are plotted employing logarithmic scale.Therefore actively moving particles, such as motile bacteria whosevelocities are considerably higher than velocities typically associatedwith Brownian motion, can be screened by a system of the invention.Furthermore, In accordance with the method of the present invention apreferable exposure time in which a speckles image is sampled in suchscattering measurements is considerably smaller than a typical timecycle resulted from the frequency distribution associated with theBrownian motion.

EXAMPLE 3

An exemplary experiment displaying the features of the method and systemof the invention related to the dynamics of the light scattered fromfluids containing bacteria is described below. Two samples are takenfrom the same specimen of urine, which is free from bacteria. Acalibrated quantity of E-coli is introduced into one of these samples,such that the bacterial concentration in the sample is 10⁶colony-forming units per milliliter (CFU/ml). A quantity pf particles ofa size of 2 μm is introduced into the other sample of urine, such thatthe concentration of the particles equals the bacterial concentration ofthe first sample. These particles are made of polymethylmethacrylate(PMMA). The two samples are mechanically filtered to exclude particleslarger than 5 μm. The samples are examined with a system for detectingbacteria of the invention whose light source consists of a laser diodeof 650 nanometers (nm) having a power of 0.2 milliwatt (mw) and a beamdiameter of 0.5 mm. A two dimensional CMOS sensor serves as the lightdetector. The samples of fluids are filled into cuvettes of the firsttype such as cuvette 74 shown in FIG. 3A to which reference is againmade. The dimensions of the illuminated volume of fluid spacing betweenthe aperture of diaphragm 76 and light obscuring means 70 are the sameas described hereinabove.

Reference is now made to FIGS. 8A-8C. In FIG. 8A the intensities ofsignals of light scattered by the sample including E-coli are shown. Thesignals received by a segment of a row of pixels disposed across theface of the light detector; are periodically sampled at a rate of 300 Hzalong a time interval of one second. In FIG. 8B the intensities ofsignals of light scattered by the sample including PMMA particles areshown. The signal are received by the same segment of pixels andsimilarly sampled and plotted as in the case shown in FIG. 8A. Themagnitude of the measured intensity is represented by the colour of theplots ranging from black for zero intensity to white for maximalintensity measured. Any point along a line that is parallel to axis 148corresponds to the same point in time, whereas any line parallel to axis149 corresponds to the same scattering angle, or the same pixel withinthe segment of the row of pixels.

A series of almost horizontal lines whose colour periodically changes ina moderate rate is shown in FIG. 8B. Such temporal behavior correspondsto a substantially narrow frequency distribution of the time dependentintensity of the scattered light. Such behavior is typical in cases inwhich the particles such as the PMMA particles move in a Brownianmotion. E-coli bacteria are motile and are capable to move atsignificantly higher speeds. Therefore the corresponding frequencydistribution is considerably broader in which higher frequencies have aconsiderable contribution in making FIG. 8A look noisy and spiky.

Intensity-time profiles related to these two samples are shown in FIG.8C. The intensities of a signal received in an exemplary pixel (which isone of the pixels associated in generating FIG. 8A), are measured inarbitrary units. The intensity scale is linear and the time is measuredin seconds (SEC). Plot 150 corresponds to the sample including E-coliwhereas plot 152 to the sample including PMMA particles. Plot 150 isshifted aside from plot 152 (for graphical purposes). The considerablyhigher frequencies induced by the bacterial motility significantlycontribute to the temporal behaviour of plot 150. Whereas theconsiderably low frequencies in the range of a few Hertz induced by theBrownian motion of the PMMA particles provide for the moderate timedependence of plot 152. Aided by such intensity plots as FIGS. 8A-8C anoperator can select an exposure time and a sampling rate in whichspeckles images are to be received.

EXAMPLE 4

An experiment demonstrating features of a method for data processingaccording to a preferred embodiment of the present invention isdescribed below. An exemplary calibrated specimen of urine containingE-coli is prepared. The system employed in this experiment is describedin example 3 hereinabove. Following the procedure described in step 110and on, shown in FIG. 4 to which reference is again made, the followingactivities are made. First a sample taken from this specimen ismechanically filtered to exclude particles whose sizes exceed 5 μm. Thena portion of the filtered fluid is filled into the first test cuvette,which is a cuvette of the first type. The cuvette is placed and alignedand measurements of light scattering for detecting and counting bacteriaare made.

Reference is now made to FIGS. 9A-9C. In FIG. 9A two exemplarycalibrated scattering profiles of a set of calibrated profiles and themeasured and fitted scattering profiles of this urine sample arerespectively shown. Curve 156 represents the calibrated scatteringprofile of uninfected urine. Curve 158 represents one of the calibratedscattering profiles of urine containing bacteria at a specific bacterialconcentration level. Curve 159 represents the scattering profile fittedto the examined sample. The circles represent values of the associatedscattering profile as measured. The continuous line represents thebest-fitted linear combination of calibrated scattering profilesrepresenting urine containing bacteria at a concentration of 10⁵ CFU/ml.A considerably high level of matching is demonstrated over a significantrange of scattering angles. The detected level of bacterialconcentration in this examined sample deviated from the reference levelby a few percent.

At this stage a calibrated dose of gentamicin is such introduced thatits concentration in the test cuvette equals 1%. In FIGS. 9B and 9C twodifference plots computed following the introduction of the antibioticagent into this test cuvette are respectively shown. Two speckles imagessuccessively received at two different points in time separated by atleast 20 milliseconds (ms) are employed for each difference plot. Thedifference plots are computed by subtracting the first of each pair ofthese speckles images from the second one. In FIG. 9B a difference plotderived immediately following the introduction of the antibiotics isshown, whereas FIG. 9C shows a difference plot derived 30 minutes later.Although the signal levels in both difference plots is relatively low,speckles are clearly seen in FIG. 9B whereas FIG. 9C shows aconsiderably smoother level. A significant reduction in theconcentration of non-stationary scatterers has occurred as a result ofthe introduction of an adequate antibiotic agent. Difference plots areaveraged in time along a pre-specified time interval and or in thescattering angles across a pre-specified one, or two, dimensionalangular range according to the present invention, to give an averagederivative of the concentration of scatterers in time. The temporalbehaviour of the average derivative associated with this samplecontaining E-coli is shown by reference to FIG. 9D. In FIG. 9D values ofthe averaged derivative normalised by their maximal value plotted versustime measured in minutes (MIN) are shown. A significant reduction (of afew tens of percents) in the values of the averaged derivative isdemonstrated a few minutes after the introduction of the antibiotics.

EXAMPLE 5

An analysis of the contribution of chemotaxis and or thermotaxis to thedynamics of a simulated speckles image was conducted. The same modelsand physical approach as described in example 1 hereinabove wereemployed. The light detector modelled is a two dimensional CMOS sensor.The Brownian motion is modelled by particles' velocities havinguniformly distributed directions and normally distributed magnitudeswith a mean value of 0.5 μm/sec. Chemotactic or thermotactic motions aremodelled by a uniform particles' velocity of 5 μm/sec perpendicular tothe laser beam.

Reference is now made to FIGS. 10A-10B. In FIG. 10A a three dimensionalintensity—scattering angle—time profile of particles moving in the samedirection measured along a segment of a row of pixels is shown. Theintensity of the scattered light measured in each pixel is representedby a scale of black and white colours; in which black represents zerointensity and white represents the maximal intensity measured. Theexposure time is lower than 10 milliseconds and the sampling repetitionrate is 100 Hz. The length of the segment of the row of pixels employedfor simulating these profiles is 0.15 mm. The length of the timeinterval along which the simulated intensities are shown is 2 sec.Intensities shown along a line that is parallel to axis 160 are measuredat the same pixel. The intensities along a line parallel to axis 162 aremeasured at the same point in time.

In FIG. 10B an intensity—scattering angle—time profile induced byparticles moving in a Brownian motion and also having the same constantvelocity component of 5 μm/sec. An averaged component of aunidirectional collective motion that exceeds 2 μm/sec isdistinguishable and is different from velocities typically associatedwith the Brownian motion. Therefore such analysis of speckles images canalso be used for studying the dynamics of bacteria by means of a systemof the invention. However it is clearly demonstrated that by inducingchemotactic or thermotactic motion the sensitivity of for detecting andfurther measuring the concentration of motile bacteria suspended in theexamined fluid, as well as for determining their susceptibility toantibiotic agents is considerably enhanced. By suitably selectingexposure times and repetition rates for receiving the speckle images insuch cases, the patterns of the difference plots as well as patterns ofthe respective average derivatives of concentration of scatterers overtime are more distinct. Therefore by employing suitably selectedrepetition rates and exposure times the signal to noise ratios in whichthe intensity of scattered light is measured are considerably improved.

1. A method for detecting bacteria suspended in a biological fluid inwhich a portion of said biological fluid is filtered to excludeparticles larger than said bacteria and a sample of said filteredportion is contained in a cuvette having at least one window illuminatedwith a coherent and collimated light, said method comprising the stepsof: a. repeatedly measuring at a predefined repetition rate theintensity of light scattered by said sample at least at one scatteringangle; b. calculating a difference plot of the light intensitymeasurements at said at least one scattering angle by calculating theabsolute value of the difference between an intensity level of lightmeasured at a first time at said at least one scattering angle and anintensity level of light measured at a second time at said at least onescattering angle, said difference plot calculated such that stationaryparticles are excluded from the difference plot and non-stationaryparticles are preserved in the difference plot; and c. matching saiddifference plot with a calibration curve to provide an estimate of theconcentration of the bacteria in the sample.
 2. A method as in claim 1,wherein said repeatedly measuring is accomplished at a plurality ofscattering angles to establish a scattering profile for said sample. 3.A method as in claim 2, further comprising matching said scatteringprofile with pre-stored standard scattering profiles.
 4. A method as inclaim 1, wherein said measuring is carried out regarding at least onespecific wavelength.
 5. A method as in claim 1, wherein saidilluminating is effected by at least one laser diode.
 6. A method as inclaim 1, further comprising introducing an antibiotic agent into saidsample prior to said measuring.
 7. A method as in claim 6, furthercomprising calculating an averaged derivative of concentration ofscatterers in time for said sample.
 8. A method as in claim 1, furthercomprising introducing a chemo-effector into said sample prior to saidmeasuring.
 9. A method as in claim 1, further comprising inducing atemperature gradient across said sample prior to said measuring.
 10. Amethod as in claim 1, wherein said at least one window characterized byan optical feature selected from a group of optical features consistingof transparency within a range of wavelengths containing a wavelength ofsaid illuminating light, the root mean square (RMS) value of the surfaceroughness of a face of said window does not exceed one nanometer, thequality of a face of said at least one window defined by a scratch/dignumber does not exceed 40/20, homogeneity of the index of refractionwithin said window is better than 0.0001 and any combination thereof.11. A method as in claim 1, wherein said bacteria are suspended in saidbiological fluid during both said first time and said second time.